PROCEEDINGS of International Conference on Drug Discovery and Development 2024

13^th – 14^th May 2024

Venue: Ascott Gurney Penang
Theme: Drug Discovery and Delivery: Present and Future

Editors

• KHAIRUL NIZA BINTI ABDUL RAZAK
• FAUZIAHANIM BINTI ZAKARIA
• AMIRAH BINTI MOHD GAZZALI
• CHAN SIOK YEE

CONTENTS

IC3D001
Identification And Characterization Of NSP8 As A Potential Broad-Spectrum Vaccine  Candidate Against Human Coronaviruses

IC3D002
Analysis and Development of a Universal Multi-epitope Immunogen against Multidrug-resistant (MDR) Acinetobacter baumannii

IC3D003
Universal Immunogen Design Against Human Coronaviruses by Harnessing Structural Vaccinology Approach

IC3D004
A Relationship Exists Between Plasma Testosterone Level and Testicular 11-Hydroxysteroid Dehydrogenase Oxidative Activity in Rats Administered with Morphine.

IC3D005
Exploring The Anticancer Potential Of Andrographolide: A Molecular Docking Study On Mapk14 And Egfr Tyrosine Kinase Enzymes

IC3D001
Identification And Characterization Of NSP8 As A Potential Broad-Spectrum Vaccine  Candidate Against Human Coronaviruses
Ada Kazi¹, Zakaria Ismail^1,2, Chin Peng Lim^1,3, Chiuan Herng Leow³, Chiuan Yee Leow¹*

¹ School of Pharmaceutical Sciences, Universiti Sains Malaysia, 11800 Malaysia

² Faculty of Health Sciences, Universiti Teknologi MARA, Cawangan Pulau Pinang Kampus Bertam,  13200, Kepala Batas, Penang, Malaysia

³ Institute for Research in Molecular Medicine (INFORMM), Universiti Sains Malaysia, 11800 Malaysia

*Corresponding author: Leow Chiuan Yee

Email: yee.leow@usm.my

ABSTRACT

Background and Objective: SARS-CoV-2, a high mutation RNA virus, drives new variants that are escalating global infectious cases. Genetic modifications aid host adaptation, thus evading vaccine-induced immunity. Therefore, designing a broad-spectrum vaccine could address the current vaccine limitations. Leveraging immunoinformatics and in-silico structural analysis has streamlined the identification and design of potential vaccine candidates, thereby enhancing vaccine efficacy. Non-structural proteins (NSP) can be potential targets for therapy as they are pivotal for viral replication. This study identifies potential T-cell epitopes from antigenic conserved regions of NSP8, characterised and studied for their interaction with TLR-3 to determine their potential as vaccine candidates. Method: The protein sequence of NSP8 originated from SARS-CoV-2, its variants, and SARS-CoV were retrieved from the NCBI database. Phylogenetic analysis was performed using MEGA11 software. Clustal Omega and GISAID servers were used to assess sequence conservancy and mutation rate while Vaxijen V2.0 was used to determine the antigenicity of conserved peptides. IEDB server was used to predict T-cell epitopes, I-TASSER, and GalaxyRefine refined 3D structure. Models were validated using ProSA. HawkDock facilitated docking against TLR-3, and ChimeraX visualised binding interactions of the docked complexes. Results and Discussion: The NSP8 protein of the SARS-CoV-2 contained two antigenic conserved regions, with 97.50 – 100% sequence identity across variants and SARS-CoV. 12 antigenic MHC class I and 24 antigenic MHC class II epitopes were identified. However, with stringent epitope characterisation, only 3 MHC class I and 12 MHC class II epitopes were considered. The 3D structure of antigenic conserved regions was predicted, refined, and validated as good quality. The model docked with TLR-3 showed binding energy from –44.11 kcal/mol to 0.8 kcal/mol. The selected peptide had moderate affinity. Conclusion: The epitope prediction and docking results highlight promising antigenic regions in NSP8, suggesting its potential as a broad-spectrum vaccine candidate. Further, in-vitro and in-vivo analyses are essential to ascertain immunological impact.

Keywords: Mutation, Non-structural protein, Immunoinformatics, Vaccine candidate 

INTRODUCTION

Coronavirus, RNA viruses, have evolved from causing mild respiratory infections to major outbreaks, with SARS-CoV-2 being the most significant [1]. Despite vaccines, new variants pose a threat to vaccine efficacy due to the virus’s ability to mutate rapidly [2]. Innovative approaches in the post-genomic era have transitioned from traditional methods to reverse vaccinology. Molecular biology and sequencing technologies have enabled streamlined testing and screening of microbial genome data using high-throughput -omics techniques to identify potential vaccine targets [3]. Non-structural proteins of the virus are known to play a vital role in viral replication and can be considered potential targets for therapy [4]. This study has identified potential T-cell epitopes from antigenic conserved regions of NSP8, characterised and studied for their interaction with TLR-3 to determine their potential as vaccine candidates. 

METHOD

The protein sequence of NSP8 originated from SARS-CoV-2, its variants, and SARS-CoV were retrieved from the National Center of Biotechnology Information (NCBI) database. Phylogenetic analysis was performed using MEGA11 software to determine the evolutionary relationship between the strains. Clustal Omega (https://www.ebi.ac.uk/jdispatcher/msa/clustalo) and GISAID (https://gisaid.org/database-features/covsurver-mutations-app/)  servers assess sequence conservancy and mutation rate. The antigenicity of the highly conserved region was predicted using the VaxiJen v2.0 server (http://www.ddg-pharmfac.net/vaxijen/VaxiJen/VaxiJen.html). Highly conserved regions with a score of >0.4 were selected for T-cell epitope prediction. CD4+ and CD8+ T-cell epitopes were predicted using the IEDB server (https://www.iedb.org). MHC class I and MHC class II epitopes that fell within the percentile rank ≤1% and ≤10%, respectively, were shortlisted. Using VaxiJen v2.0, AllerTOP v2.0 (https://www.ddg-pharmfac.net/AllerTOP/index.html), AllerFP v1.0 (https://www.ddg-pharmfac.net/AllergenFP/index.html), AlgPred2.0 (https://webs.iiitd.edu.in/raghava/algpred2/batch.html) and Toxin Pred server (https://webs.iiitd.edu.in/raghava/toxinpred/design.php) stringent epitope characterisation was done.

The 3D structure was predicted using the I-TASSER server (https://zhanggroup.org/I-TASSER/) and refined using GalaxyRefine from the GalaxyWEB server (https://galaxy.seoklab.org/cgi-bin/submit.cgi?type=REFINE). The refined model was then validated using ProSA (https://prosa.services.came.sbg.ac.at/prosa.php). The model was then docked against toll-like receptor-3 (TLR-3) using the HawkDock server (http://cadd.zju.edu.cn/hawkdock/) to predict their attachment. The interaction between the protein construct and TLR-3 was visualised using PDBsum (https://www.ebi.ac.uk/thornton-srv/databases/pdbsum/) and ChimeraX (https://www.rbvi.ucsf.edu/chimerax/).

RESULTS AND DISCUSSION

This study focused on NSP8 of SARS-CoV-2, its variants, and the previous SARS-CoV strain (Table I). Phylogenetic and mutation analysis showed that the strains were closely related, while SARS-CoV shared 97.50% similarity with SARS-CoV-2.

Table 1. List of coronavirus strains in this study

Strain	WHO label
SARS-CoV	–
Wuhan-Hu-1	–
B.1.17	Alpha
B.1.315	Beta
P.1	Gamma
B.1.617.2	Delta
BA1	Omicron Omicron Omicron Omicron Omicron
BA2
BA4
BA5
BA 2.12.1

Highly conserved regions of NSP8 were identified and labelled as N1 and N2. Epitope prediction and characterisation of MHC – class I and class II for selected peptides were carried out separately, and then the regions were combined to get the overall evaluation. A total of 15 epitopes were identified (Table II) that fulfilled the antigenicity, allergenicity, and toxicity prediction tests, indicating the reliability and safety of selected regions as promising vaccine candidates. To ease future in-vivo investigation, the region was expanded and labelled as ExN, and further in-silico prediction was subjected to it.

Table II. Number of T-cell epitopes

Conserved region	Length		MHC-I	MHC-II	TOTAL
N1	60		2	10	12
N2	18		1	2	3
Overall			3	12	15

To investigate the interaction of the region with Toll-like receptor (TLR-3), a 3D model was created and refined using the in-silico tool (I-TASSER) and (GalaxyRefine). Validation of the refined model by ProSA predicted the model to be within the range of average native proteins of similar size in the database with a Z-score of -4.44 (Figure I). Overall, the construct was of good quality and was subjected to in-silico docking prediction.

The docking prediction between ExN and TLR-3 indicated a strong bond, with the formation of 4 salt bridges (Lys171-Asp64, Arg222-Asp42, Lys243-Asp29, and Arg296-Asp73) and 3 strong hydrogen bonds (Arg222-Asp42, Glu272-Thr78, and Lys243-Asp29) (Figure II). The docking result indicated that the region would facilitate antigen detection and immune induction via the TLR-3 mechanism.

Figure I. (A) The 3D refined model constructed using I-TASSER and refined with GalaxyRefine. (B) The Z-score of the refined model fell within the average range scores of native structures.

Figure II. Molecular interaction between ExN (green) and TLR3 docked (turquoise) complex. (A) Interaction between interface residues of ExN and TLR3 using PDBsum. (B) Detailed binding interactions between ExN8 (Purple bonds) and TLR-3 (Red bonds) visualized using ChimeraX.

CONCLUSION

Epitopes from highly conserved regions of the non-structural protein 8 were identified and could be considered as potential vaccine candidates that could be used to design a broad-spectrum vaccine. The antigenic conserved regions displayed promising docking results. The study provides insight into the interaction with TLR-3 that contributes to vaccine design. Consensus epitope identification, in-vitro and in-vivo validation are the future courses of this study, which will design a chimera vaccine candidate and examine its immunological function.

ACKNOWLEDGEMENTS

The authors acknowledge the Ministry of Higher Education (MOHE) grant support for the Prototype Development Research Grant with Project Codes: Fundamental Research Grant Schemes with Project Codes: FRGS/1/2022/SKK0/USM/02/5.

REFERENCES

1. Abdelmageed, Miyssa I., Abdelrahman H. Abdelmoneim, Mujahed I. Mustafa, Nafisa M. Elfadol, Naseem S. Murshed, Shaza W. Shantier, and Abdelrafie M. Makhawi. 2020. “Design of a Multiepitope-Based Peptide Vaccine against the e Protein of Human COVID-19: An Immunoinformatics Approach.” BioMed Research International 2020. https://doi.org/10.1155/2020/2683286
2. Organisation, World Health. 2022. “Tracking SARS-CoV – 2 Variants.” 2022. https://www.who.int/en/activities/tracking-SARS-CoV-2-variants/
3. He, Yongqun, Rino Rappuoli, Anne S. De Groot, and Robert T. Chen. 2010. “Emerging Vaccine Informatics.” Journal of Biomedicine and Biotechnology 2010. https://doi.org/10.1155/2010/218590
4. Yadav, Rohitash, Jitendra Kumar Chaudhary, Neeraj Jain, and Pankaj Kumar Chaudhary. 2021. “Role of Structural and Non-Structural Proteins and Therapeutic,” 1–16.

IC3D002

 Analysis and Development of a Universal Multi-epitope Immunogen against Multidrug-resistant (MDR) Acinetobacter baumannii

Zakaria Ismail^1,2, Ada Kazi¹, Lim Chin Peng³, Chiuan Herng Leow, Leow Chiuan Yee¹*

¹ School of Pharmaceutical Sciences, Universiti Sains Malaysia, 11800 Malaysia

² Faculty of Health Sciences, Universiti Teknologi MARA, Cawangan Pulau Pinang Kampus Bertam, 13200, Kepala Batas, Penang, Malaysia

³ Institute for Research in Molecular Medicine, Universiti Sains Malaysia, 11800, Gelugor, Penang

*Corresponding author: Leow Chiuan Yee

*Corresponding author: Leow Chiuan Yee

Email: yee.leow@usm.my

ABSTRACT

Background and Objective: Acinetobacter baumannii is a Gram-negative bacterial species commonly associated with hospital-acquired infections, especially among critically ill patients. This pathogen has gained attention due to its propensity to develop diverse immune evasion mechanisms and resistance to multiple antibiotics, including carbapenems and colistin. The global surge of multidrug-resistant (MDR) A.baumannii poses a significant threat and becomes a primary contributor to the rising morbidity and mortality rate in healthcare settings. Currently, there is no licensed vaccines or potential candidates identified in the clinical trial stage. Vaccine, therefore, emerges as a promising alternative strategy, offering robust, long-term protection against MDR A. baumannii infections. This study aims to identify the conserved surface proteins of A.baumannii broad-spectrum immunogen development. Method: This study involved comprehensive in-silico analysis that combines pan-genomic, subtractive proteomics and reverse vaccinology approaches. Results and Discussion: Pangenome analysis of 213 A.baumannii genomes retrieved from the National Center for Biotechnology Information (NCBI) database resulted in 1687 core proteomes that can potentially act as vaccine candidates. The reverse vaccinology approach successfully prioritised five significant potential proteins, consisting of peptidoglycan DD-metalloendopeptidase protein, M23 family metallopeptidase, Efflux transporter outer membrane subunit, TonB-dependent receptor, and TolC family outer membrane proteins. Based on the database essential gene (DEG) and literature, these proteins were crucial to the pathogen’s survival, making them the most potential candidates. The selected proteins were subjected to epitope mapping, and 14 potential B-cell-derived T-cell epitopes were identified and shortlisted for multiple epitope vaccine construct. Conclusion: The integration of pan-genomic and reverse vaccinology approaches has identified five significant conserved antigenic surface proteins. 14 potential epitopes were successfully derived from the identified proteins and shortlisted to design a multi-epitope vaccine against MDR A.baumannii. Further analysis with molecular docking and in vivo analysis is underway to verify the immunogenicity of the vaccine candidate. 

Keywords: Acinetobacter baumannii; Multi-drug resistance; Pan-genomic; Reverse vaccinology; Multi-epitope vaccine

INTRODUCTION

Acinetobacter baumannii is a gram-negative, non-fermenting bacterium that is commonly isolated in intensive care units, particularly among critically ill patients [1]. This pathogen has become increasingly concerning due to its global emergence of multidrug resistance toward existing therapeutic drugs. The resistance of A. baumannii, including carbapenems, severely restricts treatment options, with colistin representing the last viable antibiotic option against this bacteria [2]. However, reports of colistin resistance strains have surged in recent years [3]. Recognising the criticality of A.baumannii infection, especially carbapenem-resistant strains, the World Health Organization (WHO) classified it as one of the critical pathogens since 2017 [4], necessitating innovative strategies for combatting the infection.

The vaccine offers promising as an alternative strategy against MDR A. baumannii, currently, no licensed vaccines targeting this pathogen are available. Despite widespread efforts to develop a vaccine, previous candidates have exhibited inadequate attenuation or provided only partial protection in preclinical evaluation [5]. Surface proteins have emerged as favourable targets for vaccine development due to their positioning on the surface, which makes them accessible to the host cells. Given the significant role played by these proteins in bacterial pathogenesis, they are being recognised as potential vaccine candidates against MDR A.baumannii infection.

This study aims to comprehensively screen and identify multiple potential immunogenic subunit epitopes to facilitate effective vaccine development. Employing pan-genomic, reverse vaccinology and subtractive proteomic approaches, we seek to address the challenges associated with A.baumannii vaccine development and pave the way for robust and long-term protection against this formidable pathogen.

METHOD

Data Retrieval and Pangenome Analysis

The protocol approach utilised in this study was adapted from previous work by Dar et al. [6] and Shahid et al. [7] with necessary modifications tailored to suit the specific objective of our study. Genomics datasets for A. baumannii were retrieved from the National Center for Biotechnology Information (NCBI) database in September 2022. Elimination of redundant genomes was carried out, followed by taxonomic annotation analysis using GTDB-Tk (https://github.com/Ecogenomics/GTDBTk). Subsequently, checkM (https://github.com/Ecogenomics/CheckM) was employed for genome completion and contamination metrics screening to isolate genomes of sufficient quality. Genomic annotation was performed using Bakta version 1.7.0 (https://pypi.org/project/bakta/0.2/), and pangenome analysis was conducted using Roary version 3.11.2 (https://sanger-pathogens.github.io/Roary/). The shortlisted core proteomes underwent further analysis with reverse vaccinology techniques for protein selection.

Reverse Vaccinology for Protein Prioritisation

Proteins identified from pangenome analysis underwent a series of reverse vaccinology screening parameters. BLASTp (https://blast.ncbi.nlm.nih.gov/Blast.cgi?PAGE=Proteins) was utilised to shortlist potential targets based on non-homology to humans. Subcellular localisation of surface proteins was determined using PsortB version 3.0 (https://www.psort.org/psortb/) and Gneg-mPLoc version 2.0 (http://www.csbio.sjtu.edu.cn/bioinf/Gneg-multi/). Essential functions were evaluated using the Database of Essential Genes (DEG) (http://origin.tubic.org/deg/public/index.php), followed by assessment for virulence and pathogenesis using the Virulence Factor Database (VFDB) (http://www.mgc.ac.cn/VFs/). Immunogenic proteins were further evaluated for membrane helices with TMHMM version 2 (https://services.healthtech.dtu.dk/services/TMHMM-2.0/), and protein molecular weight was measured with the ExPASy ProtParam tool (https://web.expasy.org/protparam/). The list of proteins meeting all the standard filtering criteria underwent further analysis for B cell and MHC epitope isolation.

Prioritisation of B-cell Derived MHC II and I Epitopes

The ABCPred server (http://crdd.osdd.net/raghava/abcpred/) filtered the potential B-cell epitopes with a threshold > 0.51 for further evaluation. Propred server (http://crdd.osdd.net/raghava/propred/) was utilised to prioritise the B-cell derived MHC II epitopes, identifying CD4+ T-cell epitopes, with antigenicity value assessed using the VaxiJen server (https://www.ddg-pharmfac.net/vaxijen/VaxiJen/VaxiJen.html). Binding affinity against the HLA II allele, DRB1*0101, was determined using the MHCPred server (https://www.ddg-pharmfac.net/mhcpred/MHCPred/), shortlisting based on an IC50 value < 500nM. Virulent potential was assessed using the VirulentPred server (https://bioinfo.icgeb.res.in/virulent2/predict.html), followed by the evaluation of IFN-γ activation using the IFNepitope server (http://crdd.osdd.net/raghava/ifnepitope/). Only epitopes predicted to boost IFN-gamma were shortlisted as potential vaccine targets. Propred I server (http://crdd.osdd.net/raghava/propred1/) was used to screen for potential B cell-derived MHC I epitopes, with immunogenicity predicted using the MHC I immunogenicity tool in the IEDB server (http://tools.iedb.org/processing/). Epitopes with an IC50 value <500nM were shortlisted, with final evaluation for virulent potential using VirulentPred. The epitopes with IC50 value <500nM are considered to have a good binding affinity toward MHC receptors (Adhikari, Tayebi, and Mizanur Rahman 2018).

RESULT AND DISCUSSION

A total of 6816 A.baumannii genomes were retrieved from the NCBI database. Following filtration, dereplication and phylogenetic analysis, 213 individual genomes of A.baumannii were selected for pangenome analysis. Subsequently, 1733 core genes were successfully isolated using pangenome analysis parameters sets >=95% to 100% conservancy. These conserved genes were then translated into protein sequences in PASTA format and submitted to reverse vaccinology analysis.

The conserved protein list obtained from pangenome analysis underwent the BLASTp in the NCBI database, resulting in the selection of 1687 non-homologous genomes for further analysis. This step is crucial to ensure that selected proteins do not exhibit similarity with host cells, thereby minimising the risk of autoimmune effects [8]. Subsequently, screening focused on surface protein localisation as vaccine candidates, identifying 26 potential proteins. Through a series of filtration steps involving essential genes, virulence capability, presence or absence of transmembrane helicase and molecular weight size of the proteins, five promising protein candidates were identified that met all the set parameters. These selected proteins include peptidoglycan DD-metalloendopeptidase, M23 family metallopeptidase, Efflux transporter outer membrane subunit, TonB-dependent receptor, and TolC family outer membrane proteins. These surface proteins play critical roles in biofilm formation, antibiotic resistance, and nutrient acquisition, rendering them promising targets for vaccine development to combat antibiotic resistance and impair bacterial survival [9]. The finalised proteins underwent subtractive proteomic screening to further identify active epitope regions for vaccine development.

Figure I. Demonstrate the overview of epitopes prioritisation for vaccine development against A. baumannii infections. A; Data retrieval and pangenome analysis. B; Reverse vaccinology approach. C; Subtractive proteomic screening. D; Detailed list of potential epitopes for multi-epitope vaccine development.

The Identification of active MHC class II and MHC class I epitopes from the protein target is essential for multi-epitope vaccine development. The finalised protein targets obtained from reverse vaccinology protocol were subjected to the ABCpred tool, resulting in the identification of 262 B-cell epitopes. These B-cell epitopes were further analyzed using the Propred tool for MHC class II epitopes, while the Propred I tool was employed to identify the MHC class I epitopes.  Subsequently, For MHC class II, 12 final epitopes meeting all the filtration parameters were successfully identified, whereas only two epitopes were identified for MHC class I. The previous study demonstrated a promising result obtained with titers antibodies secreted after testing synthetic multi-epitopes of surface protein constructs of Haemophilus influenzae strains in vivo analysis [10]. Figure I (A, B, C and D) illustrate the overall screening steps in the study, from data retrieval to the final list of potential epitopes as vaccine candidates.

CONCLUSION

The integration of pan-genomic and reverse vaccinology approaches has successfully identified five conserved antigenic surface proteins. Theseproteins are pivotal in bacterial pathogenesis including biofilm formation, antibiotic resistance, and nutrient acquisition. Consequently, they represent promising vaccine targets for combating antibiotic resistance and impairing bacterial survival. Subsequent filtration through subtractive proteomic analysis successfully isolated 14 antigenic, highly conserved in nature, non-toxic, high virulence epitopes, which hold huge potential for the development of multi-epitope vaccines against multiple drug-resistant A. baumannii in future.

ACKNOWLEDGEMENTS

The author acknowledges the grant support by the Ministry of Higher Education (MOHE) for the Prototype Development Research Grant with Project Codes: Fundamental Research Grant Scheme with Project Codes: FRGS/1/2021/SKK06/USM/02/12).

REFERENCES

1. Morris, Faye C., Carina Dexter, Xenia Kostoulias, Muhammad Ikhtear Uddin, and Anton Y. Peleg. 2019. “The Mechanisms of Disease Caused by Acinetobacter Baumannii.” Frontiers in Microbiology 10 (JULY). https://doi.org/10.3389/fmicb.2019.01601
2. Doi, Yohei, Gerald L Murray, and Anton Y Peleg. 2015. “Acinetobacter Baumannii : Evolution of Antimicrobial Resistance — Treatment Options.” Respiratory and Critical Care Medicine 36 (212): 1–14.
3. Novović, Katarina, and Branko Jovčić. 2023. “Colistin Resistance in Acinetobacter Baumannii: Molecular Mechanisms and Epidemiology.” Antibiotics 12 (3): 516. https://doi.org/10.3390/antibiotics12030516
4. WHO. 2017. “Global Priority List of Antibiotic-Resistant Bacteria to Guide Research, Discovery, and Development of New Antibiotics.” 2017.
5. Mat Rahim, Nor Aziyah, Hai Yen Lee, Ulrich Strych, and Sazaly AbuBakar. 2021. “Facing the Challenges of Multidrug-Resistant Acinetobacter Baumannii: Progress and Prospects in the Vaccine Development.” Human Vaccines and Immunotherapeutics 17 (10): 3784–94. https://doi.org/10.1080/21645515.2021.1927412
6. Dar, Hamza Arshad, Tahreem Zaheer, Muhammad Shehroz, Nimat Ullah, Kanwal Naz, Syed Aun Muhammad, Tianyu Zhang, and Amjad Ali. 2019. “Immunoinformatics-Aided Design and Evaluation of a Potential Multi-Epitope Vaccine against Klebsiella Pneumoniae.” Vaccines 7 (3): 1–17. https://doi.org/10.3390/vaccines7030088
7. Shahid, Fatima, Tahreem Zaheer, Shifa Tariq Ashraf, Muhammad Shehroz, Farha Anwer, Anam Naz, and Amjad Ali. 2021. “Chimeric Vaccine Designs against Acinetobacter Baumannii Using Pan Genome and Reverse Vaccinology Approaches.” Scientific Reports 11 (1): 1–15. https://doi.org/10.1038/s41598-021-92501-8
8. Uddin, Reaz, Fareha Masood, Syed Sikander Azam, and Abdul Wadood. 2019. “Identification of Putative Non-Host Essential Genes and Novel Drug Targets against Acinetobacter Baumannii by in Silico Comparative Genome Analysis.” Microbial Pathogenesis 128 (January 2018): 28–35. https://doi.org/10.1016/j.micpath.2018.12.015
9. Grandi, Guido. 2010. “Bacterial Surface Proteins and Vaccines.” F1000 Biology Reports 2 (1): 1–3. https://doi.org/10.3410/B2-36
10. Bibi, Naseeha, Amtul Wadood Wajeeha, Mamuna Mukhtar, Muhammad Tahir, and Najam us Sahar Sadaf Zaidi. 2023. “In Vivo Validation of Novel Synthetic Tbp1 Peptide-Based Vaccine Candidates against Haemophilus Influenzae Strains in BALB/c Mice.” Vaccines 11 (11): 1–16. https://doi.org/10.3390/vaccines11111651

IC3D003

 Universal Immunogen Design Against Human Coronaviruses by Harnessing Structural Vaccinology Approach

Chin Peng Lim^1,2, Ada Yousef Kazi², Zakaria Ismail², Chiuan Yee Leow², Chiuan Herng Leow¹*

¹ Institute for Research in Molecular Medicine (INFORMM), Universiti Sains Malaysia, 11800 Malaysia

² School of Pharmaceutical Sciences, Universiti Sains Malaysia, 11800 Malaysia

*Corresponding author: Leow Chiuan Herng

Email: herng.leow@usm.my

ABSTRACT

Backgrounds and Objectives: The COVID-19 pandemic has implied the mutational capability of coronavirus since a number of SARS-CoV-2 variants has been rapidly increased since 2019. Omicron variant, for example, even showed immune evasion in convalescent and vaccinated individuals, posing challenges over existing vaccines. Structural vaccinology has advantages over conventional approaches such as significant time and cost reduction and improved reliability. The viral structural proteins are acknowledged for their vital role in host-pathogen interaction, resulting them as potential vaccine candidates. The primary objective of this study is to identify and characterise antigenic conserved regions within structural proteins consisting of T-cell epitopes and potential interactions with TLR-3. Method: The sequences of structural proteins of the SARS-CoV-2 variants were retrieved from NCBI database. Conserved regions were identified and analysed for antigenicity through VaxiJen. The antigenic conserved regions were analysed for T-cell epitope prediction using IEDB tools. 3D structures were also constructed using I-TASSER and refined using GalaxyRefine. All refined structures were validated using ProSA. Lastly, the refined structures were docked against TLR-3 using HawkDock and the binding interactions were visualised using ChimeraX. Results and Discussion: The antigenic conserved regions were predicted to contain over 100 MHC Class-I epitopes and MHC Class-II epitopes. Following that, all antigenic conserved regions were proceeded for 3D structure prediction and refinement. The refined protein models were validated to have good quality. Then, each refined model was docked against TLR-3. The global energies of docked complexes fell within the range of -34.96 to -28.75 kcal/mol. Overall, the protein constructs showed good binding affinities with TLR-3. Conclusion: The antigenic conserved regions were predicted to have a significant number of epitopes and displayed promising docking results. This study provides some perspectives on the interaction of antigenic conserved peptides with TLR-3, contributing to the vaccine design. in vitro and in vivo validation are currently underway to examine the immunological function of the protein constructs.

Keywords: coronavirus; structural protein; structural vaccinology; protein construct; vaccine candidate

INTRODUCTION

High mutational rate has always been the superior attribute of coronaviruses. The recent pandemic caused by SARS-CoV-2, one of the members of the genus of betacoronavirus, has once again demonstrated this fact [1]. Although vaccines were introduced to the world at an unprecedented speed, the emergence rate of variants continued to take the lead. Immune evasion was even reported in convalescent and even vaccinated individuals. As of 17 March 2024, over 770 million cases have been recorded with seven million death. Consequently, doubt over the efficacies of existing vaccines has bursted among the public.

Advances in computational technology have skyrocketed since decades ago and nearly all aspects of our lives are benefited from this, for example immunological field. Structural vaccinology enables the identification of potential antigens from the whole array of target pathogens followed by modelling of antigens into 3D structure [2]. The computational approach eliminates the hassles of tedious, time-consuming and labour-intensive experiments. The structural proteins are acknowledged for their vital role in host-pathogen interaction, making them suitable vaccine candidates [3]. The primary aim of this study is to identify and characterize antigenic conserved regions within structural proteins consisting of T-cell epitopes and potential interactions with TLR-3.

METHOD

The sequence retrieval of SARS-CoV-2 structural proteins were conducted from National Center for Biotechnology Information (NCBI) database. The protein sequences were analysed via multiple sequence alignment (MSA) using MEGA software to identify the highly conserved regions found among SARS-CoV-2 variants in this study. The antigenicity of the highly conserved regions was predicted using the online server, VaxiJen v2.0 (http://www.ddg-pharmfac.net/vaxijen/VaxiJen/VaxiJen.html). Highly conserved regions that passed the antigenic score of 0.5 were selected for T-cell epitope prediction.

The MHC class-I restricted cytotoxic T-lymphocyte (CTL) epitopes and MHC class-II restricted helper T-lymphocyte (HTL) epitopes were predicted using recommended NetMHCpan EL 4.0 prediction method (http://tools.iedb.org/mhci/) and IEDB recommended 2.22 prediction method (http://tools.iedb.org/mhcii/), respectively. The epitopes which fall within the percentile rank ≤1% and ≤10% were shortlisted, respectively. The antigenicity prediction of epitopes was done using VaxiJen v2.0. The allergenicity and toxicity of epitopes were also analysed using online tool AllerTOP v2.0 (https://www.ddg-pharmfac.net/AllerTOP/) and ToxinPred server (http://crdd.osdd.net/raghava/toxinpred/), respectively.

The 3D structures of antigenic conserved regions were predicted using I-TASSER server (https://zhanggroup.org/I-TASSER/). The predicted 3D models were refined using GalaxyRefine module of the GalaxyWEB server (https://galaxy.seoklab.org/cgi-bin/submit.cgi?type=REFINE). The refined models were then validated with ProSA (https://prosa.services.came.sbg.ac.at/prosa.php). HawkDock server (http://cadd.zju.edu.cn/hawkdock/) was used for docking study of protein constructs against TLR-3. PDBsum (https://www.ebi.ac.uk/thornton-srv/databases/pdbsum/) and ChimeraX (https://www.rbvi.ucsf.edu/chimerax/) were then applied to visualize the interactions occurred in the docked complex of protein constructs and TLR-3.

RESULTS AND DISCUSSION

This study focuses on the variants of SARS-CoV-2 as listed in Table 1 while taking previous strains (SARS-CoV and MERS-CoV) into consideration. Basically, regions that are highly conserved and antigenic were discovered in three of the structural proteins, namely spike protein (S), nucleocapsid protein (N) and membrane protein (M). On contrary, the conserved sites in envelope protein (E) were of insignificant length and therefore excluded from this study.

Table I. List of coronavirus strains included in this study.

Virus strain	WHO label
SARS-CoV	–
MERS-CoV	–
Wuhan-Hu-1	–
B.1.1.7	Alpha
B.1.351	Beta
P.1	Gamma
B.1.617.2	Delta
B.1.1.529	Omicron
B.1.525	Eta
B.1.526	Iota
C.37	Lambda
B.1.617.1	Kappa

The antigenic conserved regions selected from S, N and M protein were termed SA1, NA1 and MA1, respectively. The sequence lengths of SA1 and MA1 were relatively shorter than NA1, as stated in Table 2. Collectively, 67 MHC Class-I-restricted epitopes and 65 MHC Class-II-restricted epitopes fulfilled the antigenicity, allergenicity and toxicity prediction tests, suggesting the promising reliability and safety of selected regions as vaccine candidates.

Table 2. Number of T-cell epitopes selected from each antigenic conserved region.

Conserved region	Length	MHC Class-I restricted	MHC Class-II restricted
SA1	121	15	23
NA1	263	33	28
MA1	118	19	14

To investigate the immunological functions and interactions of antigenic conserved regions, 3D models were created. Based on ProSA, the refined models were validated to be within the range of native proteins of similar size as shown in Z-scores (-2.64, -7.21 and -2.82, respectively). Overall, the protein constructs were of good quality, as implied by their respective Z-scores which fell within the range of scores of native structures, and ready for the in silico docking study. The protein constructs (SA1, NA1 and MA1) before and after refinement as well as their corresponding Z-scores were shown in Figure 1.

Figure 1. (A-C) The 3D models were constructed using I-TASSER from the antigenic conserved regions of S, N and M protein, respectively. (D-F) The predicted models were refined using GalaxyRefine. (G-I) The Z-scores of refined models fell within the range of scores of native structures.

Toll-like receptor 3 (TLR-3) is known to involve in the production of type I IFNs, proinflammatory cytokines, such as IL-6 and tumour necrosis factor (TNF) upon the activation with toll-interleukin receptor (TIR)-domain-containing adaptor protein-inducing interferon (IFN)-β (TRIF) [4]. Elevated expression was also reported in individuals infected with SARS-CoV-2 [5]. As we can see from Figure 2, five hydrogen bonds were present (Ser239-Gln120, His287-Thr92, His287-Tyr99, Asp322-Thr92, Asn432-Gln48) in the SA1-TLR-3 docked complex. Then, in the NA1-TLR-3 complex, seven hydrogen bonds (Glu409-Ser96, Pro455-Arg90, Gln458-Asn91, Arg459-Ala153, Glu505-Thr224, Glu562-Arg158, Lys564-Thr170) and two salt bridges (Glu508-Arg161, Glu562-Arg158) were formed. A hydrogen bond (Lys176-Thr24) and a salt bridge (Arg39-Glu82) were found in MA1-TLR-3 complex. The presence of hydrogen bonds and salt bridges suggests the stability of docking interactions between the structures [6]. The docking results imply that the protein constructs might be useful in facilitating immunity induction via TLR-3 mechanism.

Figure 2. Binding interactions between protein constructs (purple-coloured structure) and TLR-3 (green-coloured structure), illustrated with ChimeraX software. (A) SA1-TLR3. (B) NA1-TLR3. (C) MA1-TLR3.

CONCLUSION

Vaccine candidates consisting of highly conserved regions from structural proteins were proposed in this study to contribute to overcome the waning vaccine efficacies due to persistent viral mutations. The antigenic conserved regions were predicted to have a significant number of epitopes and have displayed promising docking results. This study provides some perspectives about the interaction of protein constructs with TLR-3, contributing to the vaccine design. in vitro and in vivo validation are currently underway to examine the immunological function of the protein constructs.

ACKNOWLEDGEMENTS

The authors acknowledge the grant support by Ministry of Higher Education (MOHE) for Prototype Development Research Grant with Project Codes: Fundamental Research Grant Schemes with Project Codes: FRGS/1/2022/SKK0/USM/02/5.

REFERENCES

1. World Health Organization. 2024. “COVID-19 Epidemiological Update – 15 March 2024.” 2024. https://www.who.int/publications/m/item/covid-19-epidemiological-update-15-march-2024.
2. Koff, Wayne C., Rino Rappuoli, and Stanley A. Plotkin. 2023. “Historical Advances in Structural and Molecular Biology and How They Impacted Vaccine Development.” Journal of Molecular Biology 435 (13): 168113. https://doi.org/10.1016/J.JMB.2023.168113
3. Lim, Chin Peng, Boon Hui Kok, Hui Ting Lim, Candy Chuah, Badarulhisam Abdul Rahman, Abu Bakar Abdul Majeed, Michelle Wykes, Chiuan Herng Leow, and Chiuan Yee Leow. 2022. “Recent Trends in next Generation Immunoinformatics Harnessed for Universal Coronavirus Vaccine Design.” Pathogens and Global Health. https://doi.org/10.1080/20477724.2022.2072456
4. Chen, Yujuan, Junhong Lin, Yao Zhao, Xianping Ma, and Huashan Yi. 2021. “Toll-like Receptor 3 (TLR3) Regulation Mechanisms and Roles in Antiviral Innate Immune Responses.” Journal of Zhejiang University. Science. B 22 (8): 609. https://doi.org/10.1631/JZUS.B2000808
5. Petrone, Vita, Marialaura Fanelli, Martina Giudice, Nicola Toschi, Allegra Conti, Christian Maracchioni, Marco Iannetta, et al. 2023. “Expression Profile of HERVs and Inflammatory Mediators Detected in Nasal Mucosa as a Predictive Biomarker of COVID-19 Severity.” Frontiers in Microbiology 14 (May): 1155624. https://doi.org/10.3389/FMICB.2023.1155624/BIBTEX
6. Fu, Yi, Ji Zhao, and Zhiguo Chen. 2018. “Insights into the Molecular Mechanisms of Protein-Ligand Interactions by Molecular Docking and Molecular Dynamics Simulation: A Case of Oligopeptide Binding Protein.” Computational and Mathematical Methods in Medicine 2018 (1): 3502514. https://doi.org/https://doi.org/10.1155/2018/3502514

 

IC3D004

A Relationship Exists Between Plasma Testosterone Level and Testicular 11b-Hydroxysteroid Dehydrogenase Oxidative Activity in Rats Administered with Morphine.

Khairul Niza A.R. ^1*, Nwe K.H.H.²

¹ School of Pharmaceutical Sciences, Universiti Sains Malaysia, 11800 Pulau Pinang, Malaysia.

² Department of Physiology, Faculty of Medicine, Universiti Teknologi MARA, Sungai Buloh Campus, Selangor Branch, 47000 Selangor, Malaysia, previously affiliated with the Department of Physiology, Faculty of Medicine, Universiti Kebangsaan Malaysia, 50300 Kuala Lumpur, Malaysia.

*Corresponding author: Khairul Niza Abdul Razak

Email: niza@usm.my

ABSTRACT

Background and Objective: Endogenous opioid peptides (EOP) released in response to stress are expressed in the pituitary, adrenal medulla, and gonads. In rats, the enzyme 11β-hydroxysteroid dehydrogenase (11b-HSD) protects the reproductive system from the harmful effects of stress-induced glucocorticoids by converting corticosterone to 11-dehydrocorticosterone. A decrease in the oxidative activity of testicular 11b-HSD is associated with lower plasma testosterone (T) levels, potentially leading to impotence and infertility. Corticosterone is suggested to associate with adrenomedullary hormones in reducing testicular 11b-HSD oxidative activity in rats. The effects of EOP on testicular 11b-HSD oxidative activity warrant investigation. The current study aimed to evaluate the effects of the opiate agonist morphine and the possible mechanisms of action, on the oxidative activity of testicular 11b-HSD and plasma total testosterone levels in both normal intact (N) and adrenalectomised (ADX) rats. Method: Bilateral adrenalectomy was performed on the adrenalectomised group by dorsal midline incision under light ether anaesthesia. Each experimental group (n=6) was given intramuscular injections (IM) of either morphine (10mg/kg BW), naloxone (1mg/kg BW) or a combination of both drugs either once or once daily for three consecutive days. Blood and testis were collected, and 11b-HSD enzyme bioassay and testosterone radioimmunoassay were carried out. Results and Discussion: Morphine reduced testicular 11b-HSD oxidative activity in normal intact rats (p<0.01) but increased the enzyme activity in ADX rats (p<0.01). However, plasma testosterone levels in both normal (p<0.05 after a single treatment; p<0.01 after three-day treatment) and ADX rats were reduced by morphine (p<0.05). All the reducing effects occurred via the opioid receptors since these were reversed by naloxone (p<0.05). Possibly, the increased effects of morphine on testicular 11b-HSD activity in ADX rats are regulated by testosterone as naloxone did not cause a reversal to the increment. Conclusion: These findings suggest that testosterone is involved in the regulation of testicular 11b-HSD oxidative activity in response to elevated EOP during stress.

Keywords: Morphine; Naloxone; Testicular 11β-hydroxysteroid dehydrogenase; Testosterone

INTRODUCTION

Chronic exposure to stress activates the hypothalamic-hypophyseal-adrenal axis and sympathetic nervous system, leading to elevated corticosterone and adrenaline levels [1]. An excess of corticosteroids may have adverse effects on the male reproductive system, whereby it decreases plasma testosterone (T) levelsleading to potential issues such as impotence, infertility, testicular atrophy, and inhibition of spermatogenesis [2]. The 11β-hydroxysteroid dehydrogenase (11β-HSD) enzyme plays a role in inactivating corticosterone, offering protection against stress-induced damage by converting corticosterone to 11-dehydrocorticosterone [3]. While 11β-HSD activity has been observed in various tissues, its specific role in Leydig cells of the testis remains unclear. Previous research suggests that reductions in testicular 11β-HSD oxidative activity are linked to decreases in plasma T levels [4]. Additionally, endogenous opioid peptides (EOP) released during stress were found to affect T levels, with opioid agonists and antagonists impacting these levels via opiate receptors [5]. However, the effects of EOP on testicular 11β-HSD activity remain unexplored. This study aimed to investigate the effects of the opioid agonist morphine on testicular 11β-HSD activity and plasma T levels in normal intact (N) and adrenalectomised (ADX) rats.

METHODS

Animals

Fifty-four adult male Wistar rats weighing between 200-250g were randomly assigned to different experimental groups, including normal and ADX controls. The study was approved by the Medical Research and Ethics Committee of the Universiti Kebangsaan Malaysia Medical Centre (UKMMC).

Surgical procedures

Bilateral adrenalectomy was performed via a dorsal midline incision under light ether anaesthesia, following the procedure described by Nwe et al. in 1999 [4]. Normal saline (0.9% sodium chloride) was provided as drinking water to prevent mineral deficiency after the complete removal of the adrenal glands. The completeness of the adrenalectomy was confirmed during sacrifice.

Treatment groups

Each experimental group (n=6) was treated with either morphine (10mg/kg BW) or naloxone hydrochloride (1mg/kg BW) or a combination of both drugs via intramuscular injections either for 1 day or once daily for 3 consecutive days. Rats were sacrificed 2 hours after the final injection, and blood and testis samples were collected.

11b-HSD enzyme bioassay

The testicular 11β-HSD oxidative activities were assessed by measuring the percentage conversion of corticosterone (B) to 11-dehydrocorticosterone (A), as described previously [4]. Steroids were separated by thin-layer chromatography and identified under ultraviolet light. Radioactivity was measured using a β-Liquid Scintillation counter.

Testosterone radioimmunoassay

Plasma total T concentrations were determined using a commercially available “Coat-a-Count” total testosterone kit, according to the manufacturer’s instructions.

Statistical analysis

The data were analysed using the Statistix application and expressed as the mean ± standard error of the mean (SEM) for 11b-HSD oxidative activity and mean ± 95% confidence interval (CI) for plasma total T levels. All statistical comparisons were performed between the treatment groups and their corresponding controls using ANOVA and student t-test unless stated otherwise.

RESULTS AND DISCUSSION

A key finding of this study is the reduction in testicular 11β-HSD oxidative activity induced by morphine. We observed that this reduction occurred in normal intact rats exposed to morphine for 3 days (p<0.01) (Figure I), which contrasts with its effect on T reduction even after a single morphine treatment (p<0.05) (Figure 2). The 11β-HSD oxidative activity reduction was mediated through naloxone-sensitive opiate receptors, as the enzyme’s activity returned to near-normal levels after combined treatment with naloxone (p<0.01). Conversely, morphine increased the enzyme’s oxidative activity in rats without adrenal glands (p<0.01), and this effect was not reversed by naloxone administration (Figure I). Hence, the decrease in testicular 11β-HSD oxidative activity following morphine administration may necessitate the presence of additional adrenal secretions, as demonstrated in several previous studies [4,6,7]. Earlier research has indicated that the adrenocorticotropic hormone (ACTH) [4], adrenaline [6], glucocorticoids cortisol and dexamethasone [7] can reduce testicular 11β-HSD oxidative activity when other adrenal secretions are present. Similarly, our findings suggest that morphine may indirectly decrease testicular 11β-HSD oxidative activity through other hormones produced by the adrenal glands. Therefore, these effects would be observed only in animals with intact adrenal glands.

Figure 1. The effects of morphine on testicular 11b-HSD oxidative activity in normal and ADX rats. [A / (A+B)]% was the percentage conversion of B to A. A and B stand for 11-dehydrocorticosterone and corticosterone, respectively. Values were given as means ± SEM. The treatments given were: N given daily vehicle injection (N), ADX given daily vehicle injection (ADX), N given morphine for 1 day (NM1), N given morphine for 3 consecutive days (NM3), N given morphine and naloxone for 3 days consecutively (NMN3), ADX given morphine for 3 days consecutively (AM3), and ADX given morphine and naloxone for 3 days consecutively (AMN3). ** p<0.01 compared to their corresponding controls.

We have demonstrated that morphine reduces blood T levels through its action on the opiate receptor, as this effect was blocked by naloxone administration (p<0.05 after a single treatment; p<0.01 after three-day treatment). This finding is consistent with previous research showing a similar response after a single administration of morphine at 10mg/kg BW in normal rats [5]. Additionally, we observed a more pronounced reduction after three consecutive days of treatment. Furthermore, our study showed that the plasma T levels reduction in ADX rats following morphine treatment was also reversed by naloxone (p<0.05) (Figure 2). This suggests that the effect of morphine on plasma T levels occurs directly through the opiate receptor in the testis and is independent of the adrenal gland. The increased effects of morphine on testicular 11β-HSD activity in ADX rats is probably regulated by T, as naloxone did not reverse the increment.

Figure 2. The effects of morphine on plasma total T levels in normal and ADX rats.

Values were given as means ± 95% of CI. The treatments given were: N given daily vehicle injection (N), ADX given daily vehicle injection (ADX), N given morphine for 1 day (NM1), N given morphine for 3 consecutive days (NM3), N given morphine and naloxone for 3 consecutive days (NMN3), ADX given morphine for 3 consecutive days (AM3), and ADX given morphine and naloxone for 3 consecutive days (AMN3). * p<0.05; ** p<0.01 compared to their corresponding controls.

To investigate the impact of physiological levels of EOP on testicular 11β-HSD oxidative activity and plasma total T levels, we administered naloxone for three consecutive days (Table I). Our results showed a significant increase in testicular 11β-HSD oxidative activity in ADX rats treated with naloxone compared to ADX control rats (p<0.01). This suggests that, in the absence of adrenal glands, physiological levels of EOP do not affect testicular 11β-HSD oxidative activity. Contrastingly, there were no significant changes observed in normal rats, and plasma total T levels remained unchanged in both normal and ADX rats. These findings indicate that physiological levels of EOP do not suppress T levels, consistent with an earlier study [8].

Table I. The effects of naloxone treatment for 3 consecutive days on the oxidative activity of 11b-HSD in the testis and plasma total T levels in normal and ADX rats.

Treatments	Oxidative activity of 11b-HSD (% conversion of B to A) (Means ± SEM)	Plasma total T levels (nmol / L) (Means ± 95% CI)
Normal control Normal + naloxone ADX control ADX + naloxone	40.6 ± 1.13 39.6 ± 1.80 22.9 ± 0.55 52.5 ± 1.32 **	6.4 ± 1.12 10.4 ± 1.53 2.9 ± 1.18 5.7 ± 1.68

** p<0.01 compared to the corresponding control.

CONCLUSION

This study is the first to show the impact of morphine on testicular 11β-HSD oxidative activity. Our findings indicate that morphine influences both testicular 11β-HSD oxidative activity and plasma T levels through naloxone-sensitive opiate receptors. While the effects on plasma T were direct, the reduction in testicular 11β-HSD activity required the presence of other adrenal secretions. This study similarly confirms the reciprocal relationship between plasma T levels and testicular 11β-HSD oxidative activity.

ACKNOWLEDGEMENTS

We thank Fadzilah Suratman and Zanariah Asmawi from the Department of Physiology, Faculty of Medicine, Universiti Kebangsaan Malaysia (Currently known as Universiti Kebangsaan Malaysia Medical Center (UKMMC)) for their technical assistance.

REFERENCES

1. Berger, I, Werdermann, M., Bornstein, S.R. and Steenblock, C. The adrenal gland in stress – Adaptation on a cellular level. Journal of Steroid Biochemistry and Molecular Biology 2019; 190: 198-206. https://doi.org/10.1016/j.jsbmb.2019.04.006
2. Hampl, R. and Starka, L. Glucocorticoids affect male testicular steroidogenesis. Physiol. Res. 2020; 69 (Suppl. 2): S205-S210. https://doi.org/10.33549/physiolres.934508
3. Gomez-Sanchez, E.P. and Gomez-Sanchez, C.E. 11b-hydroxysteroid dehydrogenases: A growing multi-tasking family. Molecular and Cellular Endocrinology 2021; 526: 111210, https://doi.org/10.1016/j.mce.2021.111210
4. Nwe KHH, Morat PB, Hamid A, Fadzilah S, Khalid BAK. Novel effects of deoxycorticosterone on testicular 11b-hydroxysteroid dehydrogenase activity and plasma testosterone levels in normal and adrenalectomized rats. Exp Clin Endocrinol Diabetes 1999; 107: 288-294.
5. Adams ML, Sewing B, Forman JB, Meyer ER, Cicero TJ. Opioid-induced suppression of rat testicular function. J Pharmacol Exp Ther 1993; 266(1): 323-328.
6. Nwe KHH, Morat PB, Norhazlina AW, Hamid A, Khalid BAK. Relationship between adrenocorticotrophic hormone, adrenal gland and testicular 11b-hydroxysteroid dehydrogenase activity. (Proceeding). 2^nd National Symposium on Health Sciences. Universiti Kebangsaan Malaysia. Bangi, Malaysia. 24^th-25^th April, 1998.
7. Nwe KHH, Hamid A, Morat PB, Khalid BAK. Differential regulation of the oxidative 11b-hydroxysteroid dehydrogenase activity in testis and liver. Steroids 2000; 65: 40-45.
8. Kostic C, Andric S, Kovacevic R, Maric D. The effect of opioid antagonists in local regulation of testicular response to acute stress in adult rats. Steroids 1997; 62: 703-708.

IC3D005

Exploring The Anticancer Potential Of Andrographolide: A Molecular Docking Study On Mapk14 And Egfr Tyrosine Kinase Enzymes

Sajjad Farg Kata¹, Ibrahim M. Abdulbaqi^1*,  Mohammad G. Al‐Thiabat^2*

1 College of Pharmacy, Al-Kitab University, Kirkuk 36015 Iraq.

2 Michael Sayegh Faculty of Pharmacy, Aqaba University of Technology, Aqaba, Jordan.

*Corresponding author: Ibrahim M. Abdulbaqi and Mohammad G. Al‐Thiabat

Email: ibrahim.m.abdulbaqi@uoalkitab.edu.iq ; Mohd.althiabat@gmail.com

ABSTRACT

Background and Objective: Andrographolide (ADO), a key compound derived from the Andrographis paniculata plant, is renowned in Asian herbal medicine. The plant itself is often referred to as the ‘King of Bitterness’ due to its distinct bitter properties. ADO exhibits a range of biological activities, including anti-inflammatory, anti-metastatic, anti-angiogenic, anti-proliferative, neuroprotective, and hepatoprotective effects. Given its significant therapeutic potential, ADO has been the subject of extensive research in both in vitro and in vivo studies. These investigations have suggested that ADO’s mechanisms of action may involve interaction with specific enzymes, notably the p38 mitogen-activated protein kinase (p3-MAPK) and epidermal growth factor receptor (EGFR). However, the ability of ADO to bind to the p3-MAPK and EGFR remains unexplored, both in experimental and in silico studies. This study considered the first study to explore the binding affinity of ADO towards both p3-MAPK and the EGFR enzymes and to predict the nature of the binding interaction mechanism formed between ADO and these potential targets. Method: The protein structures of p3-MAPK (MAPK14) and EGFR tyrosine kinase were obtained from the Protein Data Bank (PDB IDs: 2QD9 and 1M17, respectively). Prior to molecular docking, these proteins were processed using the PDB2PQR service to standardise histidine residues to HID/HIE, preparing them for subsequent analyses. The processed structures were then refined using AutoDock Tools; non-standard residues and water molecules were removed, missing hydrogens and Kollman charges were added, and the structures were saved in PDBQT format for docking. The chemical structure of andrographolide was sourced from the PubChem database and energy minimized using Chem3D with molecular mechanics methods for structural optimisation. Standard ligands for p3-MAPK and EGFR tyrosine kinase, complexed within respective proteins, were used as controls. These ligands were prepared by converting their formats to PDB coordinates, applying partial Gasteiger charges, and saving them in PDBQT format after charge optimisation. For both proteins, grid boxes were defined with dimensions (44 grid points in x, y, z) and centre coordinates set to (-1.859, -1.013, 23.676) for p3-MAPK/LGF and (23.103, 0.207, 53.413) for EGFR-tyrosine kinase/erlotinib, to facilitate comparative analysis. The docking was configured to utilise the rigid protein structures as the set base, and the flexible ligands were defined accordingly. The number of genetic algorithm runs was set at 100 to ensure thorough sampling. Results and Discussion: The redocking of LGF (the co-crystalized ligand) (1-[5-[[3-[2,4-bis(fluoranyl)phenyl]-6,8-dihydro-5~{H}-imidazo[1,5-a]pyrazin-7-yl]carbonyl]-6-methoxy-1~{H}-pyrrolo[2,3-b]pyridin-3-yl]-2-[(3~{R})-3-oxidanylpyrrolidin-1-yl]ethane-1,2-dione)with p3-MAPK achieved an RMSD of 1.24 Å, indicating reliable repositioning (RMSD < 2.0 Å is typically acceptable). The co-crystallized ligand displayed a notably low binding energy of -10.28 kcal/mol, suggesting strong binding affinity. Key interactions include two strong intermolecular hydrogen bonds formed by GLY110 at distances of 2.78 Å and 2.30 Å, and additional hydrogen bonds involving MET109 and ASP112, which are critical for the stability and action of LGF in the p3-MAPK complex. Furthermore, pi-sigma and numerous hydrophobic bonds contributed to the complex stability. Comparatively, ADO exhibited a binding energy of -8.42 kcal/mol when docked with p3-MAPK, which is less than LGF’s, indicating a slightly weaker but still effective binding. ADO formed hydrogen bonds with different residues, such as ALA111 and LEU104, contributing to its efficacy in binding p3-MAPK. ADO and LGF share similar binding sites but differ in bond types, with ADO lacking pi-sigma interactions noted in LGF. Erlotinib displayed an exceptional RMSD of 0.66 Å when redocked with EGFR-tyrosine kinase, suggesting high precision in docking simulation. It demonstrated a free binding energy of -7.39 kcal/mol, facilitated by hydrogen bonds with MET769 and CYS773, and pi-sigma interactions with LEU694 and LEU820. Docking of ADO with EGFR-tyrosine kinase revealed a stronger binding affinity (-8.44 kcal/mol) compared to erlotinib, underscored by five hydrogen bonds—two at a hydroxyl group of C14 with GLU738 and LYS721, two at a hydroxyl group of C3 with MET769 and GLN767, and another hydrogen bond between C19 and MET769, which may improve stability and possibly enhancing the internalization of EGFR-tyrosine kinase. This suggests that ADO could offer therapeutic benefits by augmenting EGFR-tyrosine kinase internalisation. Conclusions: Andrographolide (ADO), a prominent compound derived from a widely used Asian plant found in countries such as China, Malaysia, and India, has demonstrated diverse medicinal properties, including anti-inflammatory, antiviral, and antibacterial effects. Previous research highlights its potential in enhancing the Nrf2/HO-1 antioxidant pathway and stimulating human beta-defensins, crucial for combating bacterial infections. Furthermore, ADO has been shown to reduce EGFR receptor presence on cell surfaces, suggesting a mechanism for its therapeutic actions. Our in silico studies reinforce these findings by demonstrating a strong binding affinity of ADO with key enzymes, surpassing that of the control ligand erlotinib in interactions with EGFR-tyrosine kinase. ADO exhibited a binding energy of -8.42 kcal/mol when docked with p3-MAPK, which is slightly less than that of the co-crystallized ligand (LGF), indicating a slightly weaker but still effective binding. This binding is characterized by the formation of numerous hydrogen bonds with residues such as ALA111 and LEU104, contributing to its efficacy in binding p3-MAPK. Notably, ADO and LGF share similar binding sites but differ in bond types, with ADO lacking the pi-sigma interactions noted in LGF. The strong binding affinity observed in our studies, characterized by the formation of numerous hydrogen and hydrophobic bonds, potentially explains the pharmacological actions observed in previous in vivo and in vitro studies. These insights pave the way for future research to optimize ADO for enhanced efficacy in cancer treatment and other therapeutic applications.